Integration of Image Processing and 3D Printing for Enhanced Intracranial Malformation Detection and Surgical Planning (#1974)

Authors

Coello, Celine Jireh

Zambrano, Shelsy

Rodríguez, Mariana

Abstract

In the present study, the detection and analysis of a brain cyst were addressed through a 2D and 3D magnetic resonance image, highlighting the issues associated with intracranial malformation segmentation accuracy. The rationale was rooted in the need for detailed visualization to guide medical and surgical procedures. It was hypothesized that 3D printing of intracranial injuries models could enhance surgical planning and provide a more accurate spatial representation. The methodology focuses on the application of image processing techniques and 3D printing technology. It takes a practical and applied approach, leveraging specific tools such as 3D Slicer, MeshLab, and Ultimaker Cura to achieve the stated objectives. The overall methodology aligns with an exploratory and applied approach to address the specific issue of intracranial injury detection and analysis. The most relevant results demonstrated the effectiveness of segmentation in highlighting brain information in magnetic resonance images. The application of 3D printing facilitated the creation of three-dimensional malformation models, providing valuable tool in surgical planning, supporting the idea of improvements in preoperative visualization, patient education, and three-dimensional understanding of anatomical structures. This approach not only positively impacts the accuracy of the process but also enhances medical-patient communication by providing clear and understandable representations of medical conditions.